metadata
library_name: transformers
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Bert-Sentiment-Fa
results: []
Bert-Sentiment-Fa
This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7200
- Accuracy: 0.8549
- F1: 0.7963
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-06
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 143 | 0.5002 | 0.8588 | 0.7918 |
| No log | 2.0 | 286 | 0.5604 | 0.8549 | 0.7900 |
| No log | 3.0 | 429 | 0.5587 | 0.8588 | 0.8031 |
| 0.1184 | 4.0 | 572 | 0.6008 | 0.8588 | 0.8008 |
| 0.1184 | 5.0 | 715 | 0.6769 | 0.8549 | 0.7999 |
| 0.1184 | 6.0 | 858 | 0.6699 | 0.8627 | 0.8036 |
| 0.0634 | 7.0 | 1001 | 0.6765 | 0.8588 | 0.8005 |
| 0.0634 | 8.0 | 1144 | 0.7032 | 0.8588 | 0.8041 |
| 0.0634 | 9.0 | 1287 | 0.7172 | 0.8588 | 0.7994 |
| 0.0634 | 10.0 | 1430 | 0.7200 | 0.8549 | 0.7963 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1